Graduate Research Assist; RA

Job Summary

The Division of Epidemiology in the Department of Internal Medicine is seeking a Graduate Research Assistant to support applied research at the intersection of healthcare, artificial intelligence, and data analysis. The primary focus of this role will be large language model (LLM) and other machine learning model evaluation/deployment, clinical data pipeline development, and natural language processing-based chart abstraction. The work will be performed using publicly available data such as MIMIC‑IV, and protected data from the University of Utah Health and the Veterans Health Administration within UofU CHPC and VA VINCI secure computing environments.

This position offers meaningful opportunities to engage in translational research that directly impacts patient care and health system operations.

• FTE: 0.5 FTE (approximately 20 hours/week); potential full‑time effort during the summer semester.
• Duration:
  Initial one‑year appointment beginning mid‑May 2026.
• Tuition Benefit:
  Tuition support is available per university policy.
• Capstone/Thesis:
  This assistantship can support capstone or thesis projects aligned with the research program.
• Direct Report:
  To Dr. Senthil Nachimuthu, who will provide structured technical oversight and weekly task direction.

• Currently enrolled master’s student in computing, informatics, data science, biomedical informatics, or a closely related discipline.
• Intermediate to advanced proficiency in Python and SQL.
• Experience applying NLP or machine learning methods to real‑world datasets (e.g., clinical text, scientific text).
• Intermediate to advanced experience with Linux system administration (shell scripting, package management, user and service configuration).
• Ability to execute defined tasks independently while receiving structured technical guidance.
• Availability to attend on‑site meetings or work in person for part of the scheduled time.
• This position requires eligibility for a VA appointment to access VA research systems (e.g., VINCI). Eligibility may be limited based on citizenship or visa status.

• Develop, maintain, and optimize data processing pipelines for clinical and research datasets using Python and SQL.
• Assist with the design, training, and evaluation of machine learning models applied to healthcare problems.
• Support research workflows within established Linux‑based environments under technical supervision.
• Conduct exploratory data analysis and prepare visualizations and summary reports for research collaborators.
• Contribute to manuscript preparation, documentation, and reproducible research practices.
• Collaborate with clinical and research faculty, staff, and other trainees.
• Work within secure, access‑controlled computing environments (e.g., VA VINCI, CHPC) following data governance and compliance requirements.

Current University of Utah graduate student who is supported on the Tuition Benefit Program.

• Experience using or modifying machine learning models such as decision trees, Bayesian models, deep learning architectures, transformers, or LLMs.
• Familiarity with healthcare data standards (e.g., SNOMED CT, LOINC, RxNorm) or electronic health record systems.
• Experience with version control (Git/Git Hub) and collaborative software development practices.

Consistent with state and federal law, the University of Utah does not discriminate based upon race, ethnicity, color, religion, national origin, age, disability, sex, sexual orientation, gender, gender identity, gender expression, pregnancy, pregnancy‑related conditions, genetic information, or protected veteran’s status. The University does not discriminate on the basis of sex in the education program or activity that it operates, as required by Title IX and 34 CFR part 106.

The requirement not to discriminate in education programs or activities extends to admission and employment. Inquiries about the application of Title IX and its regulations may be referred to the Title IX Coordinator, to the Department of Education, Office for Civil Rights, or both.

Veterans’ preference is extended to qualified applicants, upon request and consistent with University policy and Utah state law. Upon request, reasonable accommodations in the application process will be provided to individuals with disabilities.